1. Field of the Invention
The present invention relates to a method for the hierarchical determination of coherent events in a seismic image.
It applies more specifically, but not exclusively, to the imaging data obtained by means of physical seismic imaging methods: seismic amplitude or attribute data, in the pre-stack and post-stack fields, the stack being a central seismic processing operation making it possible to compress the seismic data (reduction of number of data items) and acts like a powerful anti-noise filter. It is also applicable to medical, sonar, non-destructive material testing imaging data, etc.
2. Description of the Prior Art
Mathematical Morphology, developed for the same purpose as Geostatistics by Professor Georges Matheron, is based on Cartesian and topological concepts. Its principle consists in studying the morphological characteristics (shape, size, orientation, etc.) of the objects in an image. Mathematical Morphology provides the suitable language and non-linear tools for the recognition and processing of shapes in an image irrespective of its dimension (1D, 2D, 3D . . . nD).
More specifically, Mathematical Morphology provides hierarchical image segmentation tools. In fact, it enables the segmentation of images into several regions according to one or more criteria such as the amplitude, contrast, amplitude gradient, etc. The boundaries between the regions define not necessarily rectilinear segments which generally represent energetic and continuous shapes of the image.
By definition, the term “coherent event” in a 3D image will refer to a coherent surface according to continuity and energy criteria. For a 2D image, a coherent event will correspond to a not necessarily straight line.
The usual methods to determine coherent events in seismic images are generally based on so-called propagation algorithms. Seeds are positioned on the image, i.e. anchoring points on the coherent events to be determined. These seeds are generally the result, of a human interpretation. The propagation algorithms determine the entirety of each of the coherent events selected by searching in the image the paths with the greatest correlation on the basis of the seeds relating to each event. They “propagate” from point to point, pixel by pixel, the coherent events of the image. This type of algorithm may prove to be unstable, particularly in a noisy environment, and an “incorrect” path of greatest spatial correlation is sometimes quickly taken. In addition, this propagation approach is not optimal for a 3D and real-time volume interpretation of the coherent events present in seismic cubes.
A direct application of the invention relates to the quality control of a horizon pointer (coherent events corresponding to geological interfaces) on a seismic cube.
The pointer of coherent events referred to as horizons on seismic cubes is produced semi-automatically. An interpreter creates seeds which are used an anchoring points for a propagation algorithm intended to generate all or part of the “pointed” horizon. However, this type of algorithm may prove to be unstable, particularly in a noisy environment. This instability is conveyed by shifts in the pointer with respect to the local extremum corresponding to the targeted seismic event, or sometimes by more radical errors corresponding to phase jumps. These errors may have a very significant impact on the value of the amplitude or of any other attribute extracted for example within the scope of a “reservoir-oriented study”. However, reliable and quick quality control of the pointer of these horizons proves to be essential. In fact, a “reservoir-oriented study” is a reservoir imaging study, estimating the reserves contained and, as the economic implications of such studies are considerable, the accuracy of the results provided must be optimal. Minor errors may have major economic consequences.
Moreover, visual examination is unsuitable for rapidly detecting spatial anomalies extending in the three spatial dimensions.
Another possible application relates to the determination of coherent events on different seismic cubes of the same geographic zone, these cubes being generated with different processing parameters.
In the solutions presently proposed, it happens frequently in seismic processing and interpretation that two (or more) seismic cubes are defined on the same geographic zone. Depending on the operational context, the analysis of the differences between the two cubes is generally instructive. It may display differences associated with:                hydrocarbon production over time (4D, i.e. defined in the three spatial dimensions and one temporal dimension, reservoir problem);        different variable types studied such as in a 4D problem in which two types of seismic waves are propagated in the subsurface: compression waves P and shearing waves S so as to produce two cubes, one P amplitude cube and one S amplitude cube;        different processing parameters.        
The characterisation of these differences (location, quantification) is never easy, as the mere difference between the two seismic cubes often proves to be insufficient, or even futile. In fact, even slight geographic shifts in the related coherent events on each of the two seismic cubes decrease the value of the information from the difference cube considerably.